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lucashomuniz/README.md

This Portifolio presents different types of projects in the Data Analytics field each designed to address real-world business challenges and create strategic value. By leveraging technologies such as Python, R, SQL, GCP Stack, Azure Stack, AWS Stack and PowerBI, this portfolio demonstrates a unified approach to deliver efficient, scalable and impactful solutions that drive measurable business outcomes.

STATISTICAL ANALYSIS DATA VISUALIZATION MACHINE LEARNING DATA ENGINEERING
This Portifolio applies hypothesis testing, regression analysis, time series, nonparametric tests and analysis of variance to uncover patterns, trends and correlations. This Portifolio leverages advanced visualization techniques using tools like Power BI and Python to craft automatized dashboards that enhance data storytelling and Business Inteligence. This Portfolio features projects that utilize Computacional learning, employing models like Decision Trees, Random Forest and XGboost to forecast trends. This Portifolio highlights expertise in ETL Pipelines, Big Data Frameworks, Streaming Processing and Cloud Computing to ensure data is accessible, clean, and ready for advanced analytics.

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  1. Project-13 Project-13 Public

    [DATA VISUALIZATION] Enhancing Business Intelligence of a Sustainable Fertilizer Company

  2. Project-12 Project-12 Public

    [DATA VISUALIZATION] Performance Analytics and Monitoring System for Customer Service

  3. Project-06 Project-06 Public

    [MACHINE LEARNING] Data Science Techniques for Liver Disease Prediction

    Python

  4. Project-03 Project-03 Public

    [MACHINE LEARNING] Bicycle Rental Demand Forecasting with Microsoft Azure

    R

  5. Project-01 Project-01 Public

    [STATISTICAL ANALYSIS] Integrating Automation and Visualization for Optimal Data Analytics

    R

  6. Project-02 Project-02 Public

    [STATISTICAL ANALYSIS] Analyzing Delta and United Airlines Flight Punctuality

    R